Methods for strategic asset allocation by mean reversion optimization

Abstract

A computer implemented method of determining the optimal asset allocation strategy for an investment portfolio is disclosed. The optimization methodology is premised on computerized mathematical models that relate the distance from the long-term market trend at the beginning of historical periods to the returns investors ultimately receive over subsequent periods. The method incorporates a tendency of asset prices to revert to their long term trend over longer investment horizons. Applying this concept to optimizing asset allocation strategies required building software for configuring a computer to replicate this mean-reverting behavior within an optimization process and determine the distribution of expected returns from a current distance from trend.

What is claimed is: 
     
         1 . A computer implemented method of setting an asset allocation strategy, comprising:
 simulating one or more long term inflation environments using modified Monte Carlo methods using autoregressive tendencies from historical inflation data;   calculating an estimated distribution of interest rates for treasury obligations of one or more maturities;   calculating a difference between a current value and the current value predicted by a historic trend line of an asset class for one or more of equity and commodity asset classes; and   calculating an estimated distribution of equity and commodity asset class future values for one or more investment periods;   calculating an estimated distribution of risk premia over treasury obligation yields for various classes of fixed income instruments; and   estimating an estimated distribution of fixed income asset class future values for one or more investment periods;   wherein the expected asset class future values are calculated as a function of the starting yield of the asset class and the mathematical relationship between its future price and simulated changes in treasury interest rates and term risk premia over treasury rates for that asset class.   
     
     
         2 . The computer implemented method of  claim 1 , wherein calculating the estimated distribution of equity and commodity asset class future values for one or more investment periods further comprises using a modified Monte Carlo method modified by the mean reversion of the respective equity or commodity asset class. 
     
     
         3 . The computer implemented method of  claim 2 , wherein the estimated asset class future values are derived using one or more of:
 historical responses of the asset class to the current difference from the historical trend line for each investment period;   the degree of mean reversion historically observed in each asset class;   the historical impact of the interest rate and inflation environment on the rate of mean reversion; and   a random component simulated by the Monte Carlo method calculations.   
     
     
         4 . The computer implemented method of  claim 1 , wherein calculating the estimated distribution of fixed income asset class future values for one or more investment periods comprises using a modified Monte Carlo simulation of interest rates using one or more of:
 Federal Reserve (the “Fed”) policy pronouncements;   the historical relationship between long term inflation and interest rates; and   a random component simulated by the Monte Carlo method.   
     
     
         5 . The computer implemented method of  claim 1 , wherein the calculation of estimated distribution of interest rates for treasury obligations includes one or more of:
 known future Fed interest rate policy;   the historical correlation between inflation rate, Fed policy, and longer maturity interest rates;   a random component simulated by Monte Carlo methods; and   the drift in future interest rates necessary to maintain arbitrage free conditions within the simulation; and   
     
     
         6 . The computer implemented method of  claim 1 , wherein the calculation of estimated distribution of risk premia over treasury obligation yields includes:
 the historical relationship between these risk premia and inflation;   the interest rate differential between treasuries of one or more maturities;   the returns of equity asset classes; and   a random component simulated by Monte Carlo methods.   
     
     
         7 . The computer implemented method of  claim 1 , further comprising:
 determining an investment horizon based upon investment goals;   wherein one of the investment periods is the investment horizon.   
     
     
         8 . The computer implemented method of  claim 1 , further comprising:
 setting an asset allocation strategy based upon the expected distributions of one or more asset classes.   
     
     
         9 . The computer implemented method of  claim 1 , further comprising:
 setting an asset allocation strategy by allocating a portion of the value of an investment portfolio into one or more asset classes based upon the expected asset class future value; and   resetting the asset allocation strategy on a predetermined basis.   
     
     
         10 . The computer implemented method of  claim 9 , wherein the predetermined basis is an annual basis. 
     
     
         11 . The computer implemented method of  claim 2 , wherein each Monte Carlo trial of the modified Monte Carlo method comprises a set of capital market assumptions; and
 wherein the capital market assumptions of each subsequent Monte Carlo trial are recalculated based upon the results of a previous Monte Carlo trial, such that as an asset class moves away from the asset class long term trend, the capital market assumptions adjust to increase the probability of returning to trend in subsequent Monte Carlo trials.   
     
     
         12 . The computer implemented method of  claim 11 , wherein the set of capital market assumptions for equity and commodity asset classes comprise one or more of:
 expected return at a future date;   asset class volatility;   asset class correlations;   the impact of inflation on potential returns; and   the impact of interest rates on potential returns.   
     
     
         13 . The computer implemented method of  claim 11 , wherein the set of capital market assumptions for fixed income asset classed comprise one or more of:
 starting yield;   price volatility in response to changing interest rates (duration and convexity); and   a model of the asset classes term risk premia as a function of inflation, spread between yields on treasuries of one or more maturities and equity market returns.   
     
     
         14 . The computer implemented method of  claim 4 , wherein each Monte Carlo trial of the modified Monte Carlo method for fixed income asset classes is modified as interest rates change; and
 wherein higher interest rates indicate higher returns; and   wherein lower interest rates indicate lower returns.